Updating of reference magnetic signature for authenticating a document with a magnetic stripe

ABSTRACT

Methods, systems, and apparatus for accurately authenticating a document (e.g. a credit card) having a magnetic stripe are provided. The magnetic field at different points of the magnetic stripe are measured, e.g., by a checkout scanner to create a magnetic signature. Digital samples of the measurements may be used to create a representation of the magnetic signature. The representation can then be compared to reference values to produce a measure of the authenticity of the document. The reference values are updated over time to reflect changes in the magnetic stripe of the authentic document, as may occur due to physical deterioration. For example, reference values may be optimized based on recent measurements of the authenticated document to provide a more accurate determination of authenticity for future measurements.

CROSS-REFERENCES TO RELATED APPLICATIONS

This application is related to concurrently filed U.S. PatentApplications: entitled “REPRESENTING A SIGNATURE OF A MAGNETIC STRIPEFOR AUTHENTICATING A DOCUMENT” by Fang et al. (U.S. application Ser. No.12/276,212, now U.S. Pat. No. 7,967,203); and entitled “VERIFYINGCARDHOLDER IDENTITY USING SIGNATURE OF THE CARD” by Fang et al. (U.S.application Ser. No. 12/276,095, now U.S. Pat. No. 8,118,220); andentitled “AUTHENTICATION OF DOCUMENTS HAVING MAGNETIC STRIPE” by Fang etal. (U.S. application Ser. No. 12/276,224, now U.S. Pat. No. 8,104,677),the disclosures of which are incorporated by reference in theirentirety.

BACKGROUND

Embodiments of the present invention relate generally to authenticatinga document having a magnetic stripe, and more specifically toauthenticating a unique magnetic characteristic of a card (e.g. a creditcard).

Documents having a magnetic stripe have long been used for a variety ofdifferent purposes. Such documents are currently used in large numbers,e.g., credit cards, debit cards, I.D. cards, etc. Typically the magneticstripes of such cards carry recorded data relating to the use of thecard, and in some instances relating to the assigned user or owner ofthe card.

Although magnetic stripe cards are widely and successfully used incommerce and industry, counterfeiting these cards is a commonoccurrence, which can result in great losses. For example, if acounterfeiter obtains an authentic credit card (or the recorded data onthe card), the counterfeiter can create a new credit card, which couldbe used to make unauthorized transactions. Consequently, the ability toreliably verify the authenticity of a card (or other document) having amagnetic stripe is important.

One method for verifying the authenticity of a card uses certainmagnetic characteristics of the magnetic stripe to identify cards.Generally, the magnetic stripes of individual cards possess inherent,substantially unique, magnetic characteristics (often referred to as afingerprint or signature). This fingerprint is related to a noise-likecomponent that results from the manufacturing process of the magneticstripe.

Current methods convert the magnetic noise to a binary number based on ameasured magnetism of specific parts of the magnetic stripe. This binarynumber is then directly compared bit-by-bit to a reference binary numberresulting from an original scan (measurement) of the card and/orindependently to previously authenticated scans. The total of thebit-by-bit differences may then be compared to a threshold value todetermine whether the card is authentic.

A problem with the current methods is that the magnetic stripe of theauthentic document degrades over time and use. A result is that theability to accurately identify the authentic document can becompromised. This is important as a part of authenticating a document isnot only to identify non-authentic documents, but to also identify whenthe authentic document is being used.

It is therefore desirable to have methods, systems, and apparatus thatcontinue to accurately authenticate a document having a magnetic stripe,particularly even after many uses of the document.

BRIEF SUMMARY

Embodiments of the present invention provide methods, systems, andapparatus for accurately authenticating a document (e.g. a credit card)having a magnetic stripe. The magnetic field at different points of themagnetic stripe is measured, e.g., by a checkout scanner to obtain areading of the magnetic signature. Based on the measurements, arepresentation of the magnetic signature may be created in any number offormats, e.g. using a Fourier transform. The representation of themagnetic signature is then compared (e.g. by a credit card processingentity) to a reference signature (e.g. values in the samerepresentation).

To account for degradation over time and/or use, the reference signatureis updated, e.g. periodically over time or in response to other factors.As a result of the update, the new magnetic signature is compared to acombination of previously received magnetic signatures. In oneembodiment, these previously received magnetic signature used in thecombination were deemed authentic or had a high probability of beingauthentic. In this manner, the effective reference signature mayadvantageously be in a state that accurately reflects the current stateof the authentic magnetic stripe.

In one embodiment, reference values (e.g. for the digital samples or thetransform coefficients) may be optimized based on recent measurements ofthe authenticated document to provide a more accurate determination ofauthenticity for future measurements.

According to one exemplary embodiment, an authentication device receivesa set of values representing the magnetic characteristic. The receivedvalues are compared to reference values. The comparing includesdetermining an error for each received value, wherein each errorincludes a sum of contributions, each corresponding to a different setof previously received values representing the magnetic characteristic.Based on the comparison, a measure of an authenticity of the document isprovided.

Other embodiments of the invention are directed to systems, scanners,and computer readable media associated with the above-described methods.

As used herein, a continuous function is a function for which smallchanges in the input result in small changes in the output. For example,a cosine function Y=cos(X) would be continuous as a small change in Xproduces a small change in Y. However, a delta function Y=δ(X) (whichequals infinity for X=0 and equals zero otherwise) is discontinuous as asmall change from X=0 will cause a very large change in Y. Suchdescription will be familiar to one of skill in the art.

A continuous function that spans a segment (e.g. a distance along amagnetic stripe) has non-zero values for at least a plurality of pointsalong the segment. For example, although the cosine function may have azero at a particular point of the segment (depending on the offsetused), the cosine function is defined throughout all space and hasnon-zero values for other points.

A better understanding of the nature and advantages of the embodimentsof the present invention may be gained with reference to the followingdetailed description and the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A shows a document 100 including a magnetic stripe 105 accordingto an embodiment of the present invention.

FIG. 1B shows a scanner 120 according to an embodiment of the presentinvention.

FIG. 1C shows an analog signal 150 obtained from a magnetic read headaccording to an embodiment of the present invention.

FIG. 2 shows a plot 200 of an analog signal 205 that may be sampled tocreate a magnetic signature of a document according to an embodiment ofthe present invention.

FIG. 3A is a plot 300 of a LDCT basis function according to anembodiment of the present invention.

FIG. 3B is a histogram 350 of the expansion coefficients of arepresentation of a magnetic signature according to an embodiment of thepresent invention.

FIG. 4 is a flowchart of a method 400 for authenticating a documenthaving a magnetic stripe according to an embodiment of the presentinvention.

FIG. 5 is a plot 500 showing a determination of a threshold according toan embodiment of the present invention.

FIG. 6 shows a block diagram of a method for authenticating a documentaccording to an embodiment of the present invention.

FIG. 7 is a histogram 700 showing a score distribution of a simulationusing a bit-by-bit comparison of binary numbers obtained from digitalsamples of the magnetic signature.

FIG. 8 is a histogram 800 showing a score distribution of a simulationwhere scores are calculated according to an embodiment of the presentinvention.

FIG. 9 shows an exemplary system 20 according to an embodiment of theinvention.

FIG. 10 shows components or subsystems of a computer apparatus that maybe used to perform or be parts of embodiments of the present invention.

DETAILED DESCRIPTION

Embodiments of the present invention provide methods, systems, andapparatus for efficiently authenticating a document (e.g. a credit card)having a magnetic stripe. The magnetic field at different points of themagnetic stripe may be measured, e.g., by a checkout scanner to create amagnetic signature. The digital samples of the measurements can then berepresented in any number of suitable ways, e.g. a binary number orcoefficients of continuous basis functions, such as a Fourier transform.These coefficients are then compared (e.g. by a credit card processingentity) to reference coefficients to produce a measure of theauthenticity of the document. Reference values (for the digital samplesor the transform coefficients) may be based (e.g. optimized) on recentmeasurements of the authenticated document to provide a more accuratedetermination of authenticity for future measurements.

FIG. 1A shows a document 100 including a magnetic stripe 105 accordingto an embodiment of the present invention. In this embodiment, thedocument 100 is a card having a plastic substrate 110. Consumerinformation 115 such as an account number, expiration date, and consumername may be printed or embossed on the card. Document 100 may include,for example, smart cards, ordinary credit or debit cards, and storedvalue cards.

Information in the magnetic stripe may be in the form of data tracksthat are traditionally associated with credits cards. In someembodiments, such tracks include Track 1 and Track 2. Track 1(“International Air Transport Association”) stores more information thanTrack 2, and contains the cardholder's name as well as account numberand other discretionary data. Track 2 (“American Banking Association”)is currently most commonly used. This is the track that is read by ATMsand credit card checkers. The ABA (American Banking Association)designed the specifications of this track and all world banks must abideby it. It contains the cardholder's account, encrypted PIN data, plusother discretionary data.

When used for a transaction (e.g. a purchase), the card is swiped thougha scanner, for example, at a point of sale terminal. The scanner obtainsan account identifier (such as a credit card number), which is then sentfor authorization of the purchase, e.g., to a payment processing networkas described below. However, as mentioned above, data recorded on thecard may be copied to a different card.

FIG. 1B shows a scanner 120 according to an embodiment of the presentinvention. The scanner may include a channel 125 for guiding a swipe ofthe card. A magnetic read head 130 senses magnetic fields in themagnetic stripe of the card and creates an electric (analog) signalbased on the sensed magnetic fields. The magnetic fields may be theresult of data (e.g., a “1” or a “0”) recorded on the magnetic stripe.

An analog-to-digital converter 135 samples the analog signal at periodicintervals and creates a digital value based on the analog value at thesample values. The digital values may be in binary form or in any otherbase number (e.g. decimal or base 5).

A processor 140 receives the digital values and processes them to createa representation of the magnetic characteristic (signature). In oneembodiment, the representation includes digital values corresponding tospecific points of the card. In one aspect, the points are twodimensional regions of the magnetic stripe. In another embodiment, therepresentation includes expansion coefficients of continuous basisfunctions, as will be described later.

The processor 140 is communicably coupled with a network interface 145that can be communicably coupled with an external device (e.g. anauthentication device) for comparing the representation (e.g. theexpansion coefficients) to a reference representation (e.g. values froman original scan of the card). In another embodiment, the processor 140can perform the comparing. The processor 140 may be part of or be acomputing device that determines a magnetic signature of the document.Also, the processor 140 may be enclosed in a separate housing from anyscanning device.

FIG. 1C shows an analog signal 150 obtained from a magnetic read headaccording to an embodiment of the present invention. The Y (vertical)axis is the voltage of the analog signal, which corresponds to astrength and/or direction of a magnetic field created by a small part ofthe magnetic stripe. The X (horizontal) axis is time. The time doescorrespond to a particular part of the magnetic card. Which particularpart of the card that the time corresponds depends on the swipe speed ofthe card. The line 170 denotes a reference voltage, which may be zero orany other value or polarity.

The peaks 155 and 160 correspond to data that has been written onto themagnetic stripe (e.g. a bit of the account number). The space betweenthe peaks is relatively flat and includes noise 165, which may be usedas a magnetic signature of the card. U.S. Pat. No. 6,098,881 issued toDeland et al., the entire disclosure of which is incorporated herein byreference, is directed to using “relatively flat” portionsrepresentative of the remnant noise characteristics of the stripe thatare located between magnetic transitions to authenticate individualdocuments. Noise on top of the recorded data may also be used, but thismay be more difficult to separate.

The noise 165 in the space may be amplified by an amplifier in the readhead 130, between the read head and the ADC 135, or in the ADC. Thisextra amplification may be triggered to occur in between the data peaks155 and 160. Typically the data peaks 155 and 160 are sampled and turnedinto bits of 0 or 1. The digital samples of the noise 165 may be binary,decimal, or any other base number.

In one aspect, the noise 165 in the magnetic stripe is the result of themanufacturing process. To create the stripe, magnetic particles are laiddown essentially in a random orientation. Thus, different parts of thestripe will have different levels of magnetism, prior to writing dataonto the cards, thereby providing a signature for that specific card.

In one embodiment, a magnetic signature may be taken from one or morepredetermined segments of the card. For example, spaces in betweenmultiple data bits may be used. Each space may be used as a separatesignature, or as components of the same signature.

FIG. 2 shows a plot 200 of an analog signal 205 that may be sampled tocreate a magnetic signature of a document according to an embodiment ofthe present invention. As in FIG. 1C, the Y axis is the voltage of theanalog signal, and the X axis is time. The time does correspond to aparticular part of the magnetic card and depends on the swipe speed ofthe card. The line 270 is a reference voltage, which is marked as zero.In one embodiment, a sensed magnetism in one direction causes a positivevoltage, and a sensed magnetism in another direction provides a negativevoltage (relative to the reference voltage 270).

As mentioned above, the analog signal 205 is sampled at periodicintervals, e.g., by the ADC 135. Points 210 show points at which adigital sample is taken. In one embodiment, the point 210(1) of theanalog signal results in a zero value. In one aspect, increases frompoint 210(1) create a positive sample value, and decreases result in anegative sample value.

In one embodiment, the point 210(2) receives a value of 1 and the point210(3) receives a value of 2. In one embodiment, the values could be 5and 9, respectively, depending on the maximum and minimum digital valuesto be used.

The digital values may then be processed, e.g. by processor 140, todetermine a representation for the magnetic characteristic. In oneembodiment, a representation would be simply using the digital samplevalues themselves. However, the number of sample values may be verylarge.

In another embodiment, the representation would look at several samplevalues over a range. For example, a range may be from 210(1) to 210(5),and an average of the values could be used to determine a new value forthat range. In one aspect, the new value could be a binary value. Insuch an instance, the binary value in this case would most likely be 1.

In another embodiment, the digital sample values are taken as points ofa function F(X_(I)), where X_(I) is a sample point. The functionF(X_(I)) is then expressed as a series (expansion) of basis functionsG(X_(I)), e.g., continuous basis functions (such as sines or cosines),providing

${F(X)} = {\sum\limits_{k = 0}^{N - 1}{C_{k}{{G_{k}(X)}.}}}$The expansion coefficients C_(K) may then be used as the representationof the magnetic characteristic in the functional space of G. Typically,the basis functions G are of a same family, such as Legendrepolynomials, Fourier functions (e.g., plane waves and sines/cosines),wavelets, and other like continuous functions.

In one embodiment, the basis functions G_(k)(X) provide a Fourierexpansion, e.g. using sines or cosines. The expansion coefficients maythen be obtained by taking a Fourier transform of the sample points,thus converting the real space representation to a Fourier spacerepresentation. An advantage of such a representation is that alignmentof the values of the representation would not be as tightly requiredrelative to the reference representation. For example, an oscillatingwaveform would have the same Fourier components even if it is shifted byan amount in real space.

One skilled in the art will appreciate the numerous different basisfunctions that may be used, such as wavelet, fast Fourier transform(FFT), local Fourier transforms, and polynomials. The basis functionsmay be orthogonal or non-orthogonal. In one embodiment, the basisfunctions will span the entire space that the sample values cover.Fourier basis functions are such a type of function as they mayrepresent any non-zero function throughout any range.

In one embodiment, the basis functions G may include a window cut offfunction. Such a window function may be used to localize the continuousbasis functions to a certain segment of real space (e.g. distance alongthe magnetic stripe). This may be desirable depending on the type oftransform or expansion that is used.

In one embodiment, local discrete cosine transforms (LDCT) are used todetermine the representation. In this case, the expansion coefficientsmay be calculated as

${{Cj} = {\sum\limits_{k = 0}^{N - 1}{A_{k}B_{k}{{Cos}\left( {\pi\frac{\left( {k + \frac{1}{2}} \right)j}{N}} \right)}}}},{{where}\mspace{14mu}\left\{ {B_{0},B_{1},\ldots\mspace{11mu},B_{N - 1}} \right\}}$is a window cut off function, {A₀, A₁, . . . , A_(N-1)} are the samplevalues, and {C₀, C₁, . . . , C_(N-1)} are the expansion coefficients. Ifthe number of basis functions is less than the number of sample points,then a fitting algorithm (such as a least squares optimization) may beused to determine the expansion coefficients.

In one aspect, a DCT (Discrete Cosine Transform) has a good informationconcentration property, which means that most of the digital informationtends to be concentrated in a few coefficients of the DCT. Such atransform can approach the Karhunen-Loève transform, which is optimal inthe de-correlation sense. Thus, using DCT, digital information can berepresented with a fewer bits.

In embodiments that use orthogonal transform, a digital signal can bemore easily transformed into a different domain without any effectiveloss of information. This is in part because adding more functionsnecessarily provides greater accuracy in the representation. Forexample, the cosine function based orthogonal transform transforms datainto a domain where its information is represented as frequencies.

FIG. 3A is a plot 300 of a LDCT basis function according to anembodiment of the present invention. As one can see, the basis functionis continuous, and it is local (not strictly zero) over a particularrange. The outer envelope 310 of the oscillating function 320 may bedefined by the window cutoff function B. The cutoff function B causesthe function to be zero or effectively zero (very small) outside of awindow, which would coincide with the segment for the magneticcharacteristic. These basis functions may be used to represent aparticular segment of a magnetic signature or all of the segments of asignature.

FIG. 3B is a histogram 350 of the expansion coefficients of arepresentation of a magnetic signature according to an embodiment of thepresent invention. The Y axis is the value of each coefficient. The Xaxis is the index value of the expansion coefficient. The histogram 350is often called a spectrum, particularly when oscillating basisfunctions are used (such as sines and cosines).

In one embodiment, fewer expansion coefficients C than sample points Aare used to represent the magnetic characteristic. For example, 128sample bits may be used, but only 32 expansion coefficients may be usedfor the representation of the signature. However, the 32 expansioncoefficients still describe the magnetic characteristic over the entirerange of the signature. In one aspect, the lowest K expansioncoefficients are sent. The spectrum of the representation is said to be32 since this is the number of basis functions used to represent thesignature.

An advantage of using coefficients of basis functions is that themagnetic signature may be represented more accurately and/or using lessnumerical values, than does a bit-by-bit representation of the magneticfield in a particular point of the magnetic stripe. Since less numericalvalues are required to be sent from a scanner to an authenticationentity, the leftover bandwidth may be used for additional data. Forexample, a non-symmetric key (which uses more data) may be used toencrypt the data.

FIG. 4 is a flowchart of a method 400 for authenticating a documenthaving a magnetic stripe according to an embodiment of the presentinvention. As mentioned above, the magnetic stripe has a distinctmagnetic characteristic that occurs over one or more predeterminedsegments of the magnetic stripe.

In step 410, the magnetic stripe of a document (e.g. a card) is scannedto create an analog signal. The scanning may occur at a checkout standusing a point of transaction (POT) terminal (such as a point of sale(POS) terminal) that includes a scanner. Note that as used herein a POSterminal may also be a POT terminal. The card is swiped though the POSterminal so that a magnetic read head reads local magnetic fields as thecard is being swiped. A time-varying analog electrical signal, whichcorresponds to the sensed magnetic fields, is thus created. In anotherembodiment, a portable device may perform the scanning.

In step 420, the analog signal is sampled to create the digital samples.For example, the ADC 135 can sample the analog signal and createcorresponding digital values. The number of sample points may be mademuch larger than the eventual representation of the signature. Thedigital values may fall within any range of numbers (e.g., −2 to 2, 0 to6, etc.).

In step 430, the digital samples of the analog signal representative ofthe magnetic characteristic are received at a processor, e.g. processor140 of a computing device. In one embodiment, the processor is in a POSterminal. In another embodiment, the processor is not in the POSterminal, but still on an internal network on which the POS terminalresides. For example, the POS terminal may be connected to a processorlocated in the same store. In yet another embodiment, the processor maybe remote from the POS terminal.

In step 440, the processor calculates a plurality of expansioncoefficients of a set of continuous basis functions based on the digitalsamples. As mentioned above, the expansion coefficients may bedetermined by performing a transform (e.g. a fast Fourier transform, orLDCT) on the digital sample values. Other fitting or optimizationalgorithms may also be used to determine the best or suitablecoefficients that when coupled with the basis functions provide theapproximate values of the digital samples.

In step 450, the expansion coefficients are sent to an authenticationdevice that compares the calculated expansion coefficients to referenceexpansion coefficients, thereby providing a measure of the authenticityof the document. In one embodiment, the expansion coefficients are sentas part of a message (e.g. an authentication request) from a POSterminal to a payment processing network.

An “authentication device” may include, for example, one or morecomputer apparatus of a payment processing network, a server computer atan issuer of a credit card (or other document), a POS terminal, or amobile phone.

In one embodiment, the scanner can perform the transformation and sendonly the prescribed coefficients, which may be relatively small comparedto the number of digital samples. Thus, bandwidth is advantageouslysaved and may be used for other purposes.

In step 460, the authentication device receives the expansioncoefficients of a set of continuous basis functions based on digitalsamples of an analog signal representative of the magneticcharacteristic. As stated above, the expansion coefficients may bereceived as part of a message that contains data recorded on thedocument (card), such as an account number. The message may be sent viaany suitable network protocols, such as TCP, IP, HTTP, SMTP, and FTP.

In step 470, the authentication device compares the calculated expansioncoefficients to reference expansion coefficients. In one embodiment, thecomparison includes a difference between each expansion coefficient andthe corresponding reference coefficient. The differences may be summed,given different weights, or provided as multiple inputs to anotherfunction. In another embodiment, a difference between functions thatreceive the expansion coefficients and the reference coefficients istaken.

In one embodiment, the authentication device may be part of the samesystem that creates the representation of the magnetic signature. Forexample, an access device (such as a mobile) phone may generate therepresentation of the magnetic signature (e.g. using a scanning deviceas described above) and perform the comparison to the referencesignature.

In step 480, based on the comparison, a measure of the authenticity ofthe document is provided. In one embodiment, the measure is a binaryresult (such as authentic or not). In another embodiment, the measure isa probability score in a range (e.g. 0 to 100) with differing valuesproviding less or more probability of the document being authentic. Themeasure may occur in discrete values (or categories) or in continuousvalues.

For example, if the expansion coefficients and the referencecoefficients are identical, then a difference could yield a zeropotentially providing a measure of 100% authenticity. Note that theresulting zero could be taken as the measure or the percentage could bereplaced by any value as a maximum score. In one embodiment, a measureproviding a 0% probability of authenticity may be defined as anyexpansion coefficients that provide a difference greater than aspecified value. In another embodiment, negative values may be used sothat there is no specified minimum as to a measure of authenticity.

In step 490, the measure may be compared to one or more thresholdvalues. In one embodiment, the measure (e.g. a score) is compared to athreshold to determine a binary result for authenticity. For example, aprobability score may be compared to a threshold; and if the score isgreater, then the document is considered authentic. In anotherembodiment, the measure may be compared to multiple threshold values toprovide discrete categories as to the level of authenticity.

The results of step 480 or 490 may then be used with other factors todetermine a final risk level of a transaction. The risk levels may bediscrete (such as binary or more categories) or continuous. For example,a probability score may be combined with other factors (such as theamount of the transaction, the merchant from which the message was sent,a history of the consumer account) to provide a risk level associatedwith the transaction. In one embodiment, the risk level may occur indiscrete values, e.g. on a scale of 1 to N (e.g. 5) or in continuousvalues. Any of the measures, risk levels, scores, or values may beprovided or displayed to other entities (such as the consumer, amerchant, or other computers involved in the transaction).

The value(s) to use as threshold may be determined by analyzing thebehavior of the measure (e.g. score) resulting from steps 480. In such amanner, a threshold may be chosen that can accurately differentiatebetween an authentic document and a non-authentic document. Thethreshold may be a static value or it may be dynamic.

FIG. 5 is a plot 500 showing a determination of a threshold according toan embodiment of the present invention. FIG. 5 shows two distributions520 and 530. The X axis is a score correlating the sensed representation(e.g. expansion coefficients when the method 400 is used) to thereference representation. A score of 100 means a highest agreement withthe reference and a 0 means a lowest agreement with the reference. The Yaxis relates a number of times (frequency) that a sensed card had aparticular score compared to a reference representation.

The distributions may be calculated using a fit to the points, or may bea simple interpolation. The fit may use any standard distributionfunctions such as a Gaussian, normal, or other suitable distribution.

The distribution 520 shows the distribution of scores from multipledifferent cards, which are not the authentic card. These scores weredetermined by swiping the cards through a scanner, comparing arepresentation of a magnetic signature, and determining the score. Thedistribution 530 is for signatures from the authentic card. These scoreswere determined from multiple swipes of the authentic card through ascanner. As one can see the score is typically not 100 all of the timefor different swipes of the same card, nor is the score 0 for all of theswipes of a different card.

In one embodiment, a threshold method searches the best position wherethe overlap of two distributions is minimized. Such a threshold methodmay provide a compromise between false negative and false positives. Inplot 500, the false negatives are the points of distribution 530 thatare to the left of the threshold line 510. The false positives are thepoints of distribution 520 that are to the right of the threshold line510. Since neither one of these inaccurate categorizations of the cardis desirable, it is generally not good to obtain zero false negatives,only to allow more false positives, or vice versa. Thus, in one aspect,the intersection of the two distributions is taken as a threshold, asshown in plot 500.

This threshold may be used as a static value for all cards of a similartype. For example, it may be determined that a threshold of 51 providesan accurate value given the distribution of scores to be expected for aparticular type of card. The threshold may also be dynamic in that a newdistribution may be determined for each new data point obtained. The newdata points may be particular to a specific card, and thus each cardwould have specific distributions, and thus different thresholds.

In one embodiment, all cards of the same type would start with the samethreshold. But, with each new score (or every N new scores) associatedwith that card, the distribution would be updated and a new thresholdcalculated. Additionally, the reference representation of the signaturemay be updated periodically as new scores are received. Such methodswill now be described.

FIG. 6 shows a block diagram of a method 600 for authenticating adocument according to an embodiment of the present invention. The stepsmay be done by different entities. For example, steps 610 and 620 may beperformed by a POS terminal, while the rest of the steps may be done byan authentication entity (such as a payment processing network).

In block 610, a sensed signature is received, or otherwise input, intothe system. In one embodiment, the input signature is the analog signalresulting from the sensing of the magnetic stripe. In anotherembodiment, the input signature is the digital sample values resultingfrom an AD conversion of the analog signal.

In block 620, the signature is transformed. In one embodiment, thedigital samples are transformed into a representation of continuousbasis functions by calculating expansion coefficients of the basisfunctions, as described herein. For example, a transformation may bemade from the real space digital samples into a frequency space spannedby the basis functions. For a frequency representation, each coefficientwould represent a different frequency of oscillation of the data pointvalues. In another embodiment, the transformation is simply a conversionof the analog input signature into digital samples.

In block 630, a measure (e.g. a score) is calculated by comparing thetransformed signature values to the reference values. The measure may becalculated in a manner as described herein. In one embodiment, thealgorithm may perform a correlation match, e.g. by calculating an error(e.g. a difference) between the values.

In one embodiment, the score is a distance, or error of an EM signatureto the reference signature, thus it is a measure of a correlation. Inone aspect, the higher score, the closer the sensed signature is to thereference signature.

In block 640, the calculated score is compared to a threshold value. Inone embodiment, the threshold (e.g. threshold 510) is calculated by theintersection of two distributions, as shown in FIG. 5. The thresholdvalue may be one that was previously received from block 680 or athreshold value that was just received from block 680 (i.e. was updatedin response to the input signature).

In one embodiment, if the score is greater than or equal to a threshold,then the signature is determined (block 650) to be a match (i.e. anauthenticated document). In another embodiment, if the score is greaterthan the threshold, then the signature is determined to be a match. Thisembodiment can be equivalent to the greater than or equal embodimentwhen threshold is lowered by one unit of accuracy.

In one embodiment, if the score is less than or equal to a threshold,then the signature is determined (block 660) to not be a match (i.e. notan authenticated document). In another embodiment, if the score is lessthan the threshold, then the signature is determined to not be a match.This embodiment can be equivalent to the less than or equal embodimentwhen threshold is increased by one unit of accuracy. Note that thematching and not matching can be reversed based on a threshold when alower score means a greater degree of matching. Also, there may bemultiple thresholds that are used to determine more than twocategorizations.

In step 670, after a score is calculated, the reference representation(values) is optionally updated. Because each time a card is swiped someadditional noise (error) may be introduced onto the signature (e.g.physically disturbing the magnetic particles of the magnetic stripe).This introduced error will lower the score of the authentic card withrespect to the reference signature, which was obtained from an originalswipe of the authentic card.

To overcome this problem, the reference signature is updated after Nauthentic input signatures have been received, where N may be anyinteger including 1. In one embodiment, the representation of eachauthenticated input signature is added into the reference. For example,a fixed amount (such as 10%) of the new, authenticated input signatureis added into the reference. In another embodiment, the amount isweighted by the score. A higher score may cause a higher amount of thatrepresentation to be added, and lower score may cause a lower amount ofthat representation to be added. A normalization may be done after thisadding.

In another embodiment, an artificial neural network (ANN) is used tooptimize the reference signature. Other optimization methods may also beused. In one aspect, the reference is updates in such way that the errorintroduced in each card swiping is minimized, and therefore, the scoreis more accurate to detect counterfeit card. In another aspect, anoptimization algorithm is used to maximize the score of the previoussignatures relative to the new reference values. The error minimizationor the score maximization may be performed for all previous inputsignatures or just for a portion of them.

Thus, the new reference values are a combination of previous inputvalues for an authenticated signature. Accordingly, when any of the newreference values (as determined by any method herein) is compared to theinput signature (e.g. coefficients), an error associated with value hascontributions from each of the previous input signatures that are usedto create the reference values.

Examples of parameters used in the ANN are as follows. One parameter isthe target value for which the optimization strives to achieve. In oneembodiment, the target value has a value close to 1. A parameter “eta”is a relatively small number (e.g. 0.01) that controls how fast the ANNconverges. A parameter “delta” is a very small number (e.g. 0.0001) thatis used to determine when to stop iteration of the ANN. A maximum numberof iterations to be allowed in ANN may be specified to prevent runawaycalculations.

In one embodiment, the correlation value from the ANN falls between −1and 1 where a “1” implies two variables are exactly same, and a “−1”implies the worst discrepancy. In other words, the closes the output isto 1 the closer to the reference signature (i.e. a match). Therefore,the closest result to one (as is practical) may be chosen as the adaptedreference signature.

In one embodiment, the score is an integer value corresponding to theoutput “Y” of the ANN. In one aspect, the score is 100 times Y, which isrounded to nearest whole-number. For example, if ANN outputs 0.91, then,the score is 91.

In one embodiment, because in real case “1” is almost impossible, avalue may be chosen that is close to “1”, e.g. 0.99. In anotherembodiment, during updating reference signature, the ANN optimize itselfto target value with error less than delta, e.g. 0.0001.

The threshold used in block 640 may also be considered a parameter sinceit is used to determine whether a particular input signature isauthentic. Since in one embodiment only authentic signatures (ones thatmatch) are used to updated the reference, the threshold affects when theANN updates the reference. Different version of the ANN may be useddepending on the type of application and the type of cards to be used.

Initial test results for the ANN scores of 0.7˜0.9 using 22 signaturesfrom the same authentic card, where 1 is a perfect match. For 120signatures obtained from different cards than the authentic card, scoreswere less than <0.2.

In one embodiment, the ANN is a nonlinear classifier having three layerswith the middle layer being hidden. In one example, input net has 32values, the middle net has 6 values, and the output net has 2 values.

In block 680, a new threshold is computed. In one embodiment, thethreshold may simply be computed by adding the new score point, anddetermining a new distribution. In another embodiment, new scores forthe previously calculated signature may be determined based on the newreference signature, and the new distribution can be calculated. Thisthreshold may then be used for the next input signature that isreceived.

In one embodiment, the threshold is updated after the change ofdistribution of scores reaches a significant level compared to thedistribution that was previously used to calculate the threshold. In oneaspect, the change is the normalized difference at each score. Such achange may occur after scores of signature of many new swipes have beenincluded in the distribution.

When 670 and 680 are used together, a degradation of the magnetic stripemay be accounted for. As mentioned above, over time, a magnetic stripemay have certain magnetic particles dislodged or removed, for example,by scratches. This could alter a signature. If the reference signaturestayed the same, then it would be more difficult to distinguish adifferent card (in effect that card has become different due to thedecay).

The decay may be seen as a shifting to the left of the distribution 530of FIG. 5. The threshold could change, but the amount of false positivesor negatives would still increase, resulting in less accuracy. By usingblock 670, the distribution 530 can be made to stay further right, thusgiving a better separation from distributions resulting from differentcards.

To illustrate the benefits of embodiments described herein, a simulationwas performed where noise was added to signatures. Distributions usingupdated reference signatures and without updating the referencesignature were compared.

In the simulation, a reference signature was chosen from a swipe of acard. For 50 iterations, noise was added to the reference signature. Foreach iteration, some amount of noise was added by randomly choosing avalue in {−2, −1, 1, 2} and adding that one value to the signature at 5random positions. Signatures for different cards (i.e. not the referencecard) were obtained by swiping those cards. No noise was added to thesesignatures of the different.

FIG. 7 is a histogram 700 showing a score distribution of a simulationusing a bit-by-bit comparison of binary numbers obtained from digitalsamples of the magnetic signature. The X axis relates a score from 0 to200, with 200 being the best match. The Y axis is the number ofsignatures that had a particular score. Each of the scores is computedfrom the original reference signature, i.e. before adding noise tosimulate additional swipes.

The scores 720 (dark data points) show the scores from different cardsthan the reference card. As one can see, the scores 720 are generallyclustered to the left of a threshold 710, which was calculated using tominimize the false positives and false negatives (also termed theoverlap). However, there are a few scores that are present to the rightof the threshold 710, which is at a score of 117.

The scores 730 (lighter data points) are the scores from the signatureswhere noise was added to the reference signature. The scores 730 aregenerally clustered to the right of the threshold 710. However, thereare a few that are present to the left of the threshold 710. The overlapis 16, thus there is a noticeable level of inaccuracy.

FIG. 8 is a histogram 800 showing a score distribution of a simulationwhere scores are calculated according to an embodiment of the presentinvention. The X axis and the Y axis are the same as in plot 700. Thescores are calculated using an LDCT representation of the magneticsignature. The scores are also calculated using a reference signaturethat was updated from the original reference signature.

As one can see, the scores 820 (dark data points) from different cardsare all clustered to the left of a threshold 810. The threshold 810 isbased on the scores shown. Notice that there are no points that arepresent to the right of the threshold 810, meaning no false positives.

The scores 830 (light data points) are the scores from the signatureswhere noise was added to the reference signature. These scores are allclustered to the right of the threshold 810. There are no points thatare present to the left of the threshold 810, which is at 112. Here allof the points are categorized accurately, as shown by a zero overlap.

FIG. 9 shows an exemplary system 20 according to an embodiment of theinvention. Other systems according to other embodiments of the inventionmay include more or less components than are shown in FIG. 9.

The system 20 shown in FIG. 9 includes a merchant 22 and an acquirer 24associated with the merchant 22. In a typical payment transaction, aconsumer 30 may purchase goods or services at the merchant 22 using aportable consumer device 32, such as a debit card, credit card, and asmartcard. The merchant 22 could be a physical brick and mortar merchantor an e-merchant.

The consumer may interact with the payment processing network 26 and themerchant through an access device 34, such as a point of sale (POS)terminal, personal computer, and a mobile phone. The merchant 22 mayalso have, or may receive communications from, an access device 34 thatcan interact with the portable consumer device 32. The access device 34may be part of, be, or include a computing device that includes aprocessor that calculates the representation of the magnetic signaturefor sending to an authentication device. The access device 34 may alsoinclude the authentication device.

Conventionally, an authorization request message, which may include therepresentation of the magnetic signature, is then forwarded to theacquirer 24, and then sent to the payment processing network 26, whichmay include the authentication device. The payment processing network 26then forwards the authorization request message to the issuer 28 of theportable consumer device 32, who sends an authorization response messageback to the payment processing network 26 to indicate whether or not thecurrent transaction is authorized. Any of the entities herein (e.g.acquirer 24, payment processing network 26, or the issuer 28) mayimplement embodiments for authenticating a card (or other document).

For example, the payment processing network 26 may perform anauthentication check, determine an authentication score, and devise arisk value, which may be based on other factors than the authenticationof the magnetic signature. In this case, the authentication device maybe any one or more computers in the payment processing network 26. Theissuer then may use the risk value to determine whether or not thetransaction is to be authorized. In another embodiment, the paymentprocessing network 26 may determine that the card is not authenticatedand then send a denial to the merchant 22 without ever contacting theissuer 28.

The payment processing network 26 can forward the authorization responsemessage back to the acquirer 24, who then sends the response messageback to the merchant 22. After the merchant 22 receives theauthorization response message, the access device 34 at the merchant 22may then provide the authorization response message for the consumer 30.The response message may be displayed by the access device 34 or theportable consumer device 32, or may be printed out on a receipt. Theresponse message may include a denial for a transaction based on thecard not being authenticated.

At the end of the day, a normal clearing and settlement process can beconducted by the payment processing network 26. A clearing process is aprocess of exchanging financial details between and acquirer and anissuer to facilitate posting to a consumer's account and reconciliationof the consumer's settlement position.

As used herein, an “acquirer” is typically a business entity, e.g., acommercial bank that has a business relationship with a particularmerchant or an ATM. An “issuer” is typically a business entity (e.g., abank) which issues a portable consumer device such as a credit or debitcard to a consumer. Some entities can perform both issuer and acquirerfunctions. Embodiments of the invention encompass such single entityissuer-acquirers.

The consumer 30 may be an individual, or an organization such as abusiness that is capable of purchasing goods or services. In otherembodiments, the consumer 30 may simply be a person who wants to conductsome other type of transaction such as a money transfer transaction or atransaction at an ATM.

The portable consumer device 32 may be in any suitable form. Forexample, suitable portable consumer devices can be hand-held and compactso that they can fit into a consumer's wallet and/or pocket (e.g.,pocket-sized). They may include smart cards, ordinary credit or debitcards (with a magnetic strip and without a microprocessor), etc. Otherexamples of portable consumer devices include, payment cards, securitycards, and access cards, and the like. The portable consumer devices canalso be debit devices (e.g., a debit card), credit devices (e.g., acredit card), or stored value devices (e.g., a stored value card).

The access devices 34 according to embodiments of the invention can bein any suitable form. Examples of access devices include point of sale(POS) devices, cellular phones, PDAs, personal computers (PCs), tabletPCs, handheld specialized readers, set-top boxes, electronic cashregisters (ECRs), automated teller machines (ATMs), virtual cashregisters (VCRs), kiosks, security systems, access systems, and thelike.

If the access device 34 is a point of sale terminal, any suitable pointof sale terminal may be used including card readers. The card readersmay include any suitable contact or contactless mode of operation. Forexample, exemplary card readers can include RF (radio frequency)antennas, magnetic stripe readers, etc. to interact with the portableconsumer devices 32.

The payment processing network 26 may include data processingsubsystems, networks, and operations used to support and deliverauthorization services, exception file services, and clearing andsettlement services. An exemplary payment processing network may includeVisaNet™. Payment processing networks such as VisaNet™ are able toprocess credit card transactions, debit card transactions, and othertypes of commercial transactions. VisaNet™, in particular, includes aVIP system (Visa Integrated Payments system) which processesauthorization requests and a Base II system which performs clearing andsettlement services.

The payment processing network 26 may include a server computer. Aserver computer is typically a powerful computer or cluster ofcomputers. For example, the server computer can be a large mainframe, aminicomputer cluster, or a group of servers functioning as a unit. Inone example, the server computer may be a database server coupled to aWeb server. The payment processing network 26 may use any suitable wiredor wireless network, including the Internet. The issuer 28 may be a bankor other organization that may have an account associated with theconsumer 30. The issuer 28 may operate a server.

Embodiments of the invention are not limited to the above-describedembodiments. For example, although separate functional blocks are shownfor an issuer, payment processing network, and acquirer, some entitiesperform all or any suitable combination of these functions and may beincluded in embodiments of invention. Additional components may also beincluded in embodiments of the invention.

FIG. 10 shows components or subsystems of a computer apparatus that maybe used to perform or be parts of embodiments of the present invention.For example, such components or any subset of such components may bepresent in various components shown in FIG. 9, including the accessdevice 34, server computers 26(a), 28(a), etc. The subsystems shown inFIG. 10 are interconnected via a system bus 1075. Additional subsystemssuch as a printer 1074, keyboard 1078, fixed disk 1079, monitor 1076,which is coupled to display adapter 1082, and others are shown.Peripherals and input/output (I/O) devices, which couple to I/Ocontroller 1071, can be connected to the computer system by any numberof means known in the art, such as serial port 1077. For example, serialport 1077 or external interface 1081 can be used to connect the computerapparatus to a wide area network such as the Internet, a mouse inputdevice, or a scanner. The interconnection via system bus 1075 allows thecentral processor 1073 to communicate with each subsystem and to controlthe execution of instructions from system memory 1072 or the fixed disk1079, as well as the exchange of information between subsystems. Thesystem memory 1072 and/or the fixed disk 1079 may embody a computerreadable medium.

Embodiments of the invention provide for a number of advantages. Forexample, less bandwidth (while no compromising accuracy) is requiredsince the data points are transformed to a function space that can moreefficiently describe the magnetic characteristic (i.e. fingerprint,signature). Also, embodiments account for the degradation of a card,thus maintaining accuracy over time.

The specific details of the specific aspects of the present inventionmay be combined in any suitable manner without departing from the spiritand scope of embodiments of the invention. However, other embodiments ofthe invention may be directed to specific embodiments relating to eachindividual aspects, or specific combinations of these individualaspects.

It should be understood that the present invention as described abovecan be implemented in the form of control logic using computer softwarein a modular or integrated manner. Based on the disclosure and teachingsprovided herein, a person of ordinary skill in the art will know andappreciate other ways and/or methods to implement the present inventionusing hardware and a combination of hardware and software

Any of the software components or functions described in thisapplication, may be implemented as software code to be executed by aprocessor using any suitable computer language such as, for example,Java, C++ or Perl using, for example, conventional or object-orientedtechniques. Computer programs incorporating features of the presentinvention may be encoded on various computer readable media for storageand/or transmission; suitable media include magnetic disk or tape,optical storage media such as compact disk (CD) or DVD (digitalversatile disk), flash memory, and the like. The computer readablemedium may be any combination of such storage or transmission devices.

Such programs may also be encoded and transmitted using carrier signalsadapted for transmission via wired, optical, and/or wireless networksconforming to a variety of protocols, including the Internet. As such, acomputer readable medium according to an embodiment of the presentinvention may be created using a data signal encoded with such programs.Computer readable media encoded with the program code may be packagedwith a compatible device or provided separately from other devices(e.g., via Internet download). Any such computer readable medium mayreside on or within a single computer program product (e.g. a hard driveor an entire computer system), and may be present on or within differentcomputer program products within a system or network.

The above description is illustrative and is not restrictive. Manyvariations of the invention will become apparent to those skilled in theart upon review of the disclosure. The scope of the invention should,therefore, be determined not with reference to the above description,but instead should be determined with reference to the pending claimsalong with their full scope or equivalents.

A recitation of “a”, “an” or “the” is intended to mean “one or more”unless specifically indicated to the contrary.

All patents, patent applications, publications, and descriptionsmentioned above are herein incorporated by reference in their entiretyfor all purposes. None is admitted to be prior art.

What is claimed is:
 1. A method for authenticating a document thatincludes a magnetic stripe having a distinct magnetic noisecharacteristic, wherein the magnetic noise characteristic exists overone or more predetermined segments of the magnetic stripe, the methodcomprising: receiving, at an authentication device, a set of valuesrepresenting a present magnetic noise characteristic of the document;comparing the received values to reference values, wherein the comparingincludes: determining an error for each received value, wherein eacherror includes a sum of contributions, each contribution correspondingto a respective set of previously received values representing aprevious magnetic noise characteristic of the document, each respectiveset of previously received values being received at a different time aspart of a respective authentication of the document; based on thecomparison, providing a measure of an authenticity of the document; andupdating the reference values with the received set of valuesrepresenting the present magnetic noise characteristic, wherein thepresent magnetic noise characteristic includes additional noiseintroduced into the magnetic stripe resulting from use of the documentsince a prior update of the reference values.
 2. The method of claim 1,wherein each contribution includes a difference between a received valueand a corresponding value of a respective set of previously receivedvalues.
 3. The method of claim 2, wherein each contribution includes arespective weighting factor multiplied by a corresponding difference. 4.The method of claim 1, wherein determining an error for each receivedvalue includes: calculating a sum of the corresponding values of thepreviously received sets; and determining a difference between thereceived value and the corresponding sum.
 5. The method of claim 1,further comprising: comparing the measure to a threshold to determine acategory of authenticity of the documents; and updating the thresholdbased on the received values.
 6. The method of claim 5, furthercomprising: receiving one or more additional sets of values representingthe magnetic noise characteristic; and computing respective measures foreach additional set of values, wherein the threshold is updated after achange of a distribution of measures reaches a predetermined level. 7.The method of claim 1, further comprising: calculating new referencevalues using the received values.
 8. The method of claim 7, whereincalculating new reference values involves using an optimizationalgorithm.
 9. The method of claim 8, wherein the optimization algorithmminimizes a total error resulting from comparing a plurality of sets ofreceived values to the new reference values or maximizes the measure ofauthenticity for a plurality of sets of received values compared to thenew reference values.
 10. The method of claim 7, wherein the receivedvalues used to calculate the new reference values are received valuesfor the document that has previously been authenticated.
 11. The methodof claim 10, wherein the new reference values are created after Nauthentic input signatures have been received.
 12. A computer programproduct comprising a computer readable medium encoded with a pluralityof instructions for controlling a computing system to perform a methodfor authenticating a document that includes a magnetic stripe having adistinct magnetic noise characteristic, wherein the magnetic noisecharacteristic occurs over one or more predetermined segments of themagnetic stripe, the instructions comprising: receiving a set of valuesrepresenting a present magnetic noise characteristic of the document;comparing the received values to reference values, wherein the comparingincludes: determining an error for each received value, wherein eacherror includes a sum of contributions, each contribution correspondingto a respective set of previously received values representing aprevious magnetic noise characteristic of the document, each respectiveset of previously received values being received at a different time aspart of a respective authentication of the document; based on thecomparison, providing a measure of an authenticity of the document; andupdating the reference values with the received set of valuesrepresenting the present magnetic noise characteristic, wherein thepresent magnetic noise characteristic includes additional noiseintroduced into the magnetic stripe resulting from use of the documentsince a prior update of the reference values.
 13. The computer programproduct of claim 12, wherein each contribution includes a differencebetween a received value and a corresponding value of a respective setof previously received values.
 14. The computer program product of claim12, wherein determining an error for each received value includes:calculating a sum of the corresponding values of the previously receivedsets; and determining a difference between the received value and thecorresponding sum.
 15. The computer program product of claim 12, furthercomprising: comparing the measure to a threshold to determine a categoryof authenticity of the documents; and updating the threshold based onthe received values.
 16. The computer program product of claim 12,further comprising: calculating new reference values using the receivedvalues.
 17. A system for authenticating a document that includes amagnetic stripe having a distinct magnetic noise characteristic, whereinthe magnetic noise characteristic occurs over one or more predeterminedsegments of the magnetic stripe, the system comprising: an input forreceiving a set of values representing a present magnetic noisecharacteristic of the document; a processor communicably coupled withthe input, the processor configured to: compare the received values toreference values, wherein the comparing includes: determining an errorfor each received value, wherein each error includes a sum ofcontributions, each contribution corresponding to a respective set ofpreviously received values representing a previous magnetic noisecharacteristic of the document, each respective set of previouslyreceived values being received at a different time as part of arespective authentication of the document; based on the comparison,provide a measure of an authenticity of the document; and updating thereference values with the received set of values representing thepresent magnetic noise characteristic, wherein the present magneticnoise characteristic includes additional noise introduced into themagnetic stripe resulting from use of the document since a prior updateof the reference values.
 18. The system of claim 17, wherein eachcontribution includes a difference between a received value and acorresponding value of a respective set of previously received values.19. The system of claim 17, wherein determining an error for eachreceived value includes: calculating a sum of the corresponding valuesof the previously received sets; and determining a difference betweenthe received value and the corresponding sum.
 20. The system of claim17, wherein the processor is further configured to: comparing themeasure to a threshold to determine a category of authenticity of thedocuments; and updating the threshold based on the received values. 21.The system of claim 17, wherein the processor is further configured to:calculate new reference values using the received values.